Real-time monitoring may be defined as the observation of measured results approximately as they happen. In many business-related activities, real-time monitoring is a goal of significant importance. For example, real-time monitoring may be an important objective in the rapidly emerging environment of automated business solutions and zero-latency management of e-business systems.
Real-time monitoring may relate to the observation of metrics and to reports or graphs. Metrics may be defined as measurable properties or as process measurements. For example, metrics may include such things as cost (e.g., the amount of a purchase order), outcome (e.g., a positive or negative result), and duration (e.g., the time required to deliver a product). Additionally, metrics can include very complex properties such as quality, performance, and the like. Further, metrics may be represented by reports or graphs. For example, a report or graph may include a figure (e.g., a bar graph) that displays metrics relevant to an operation. Each graph or report may be derived from a single metric or a plurality of metrics.
Businesses may use various computation methods to define graphs or reports that display metrics or measured properties of a business operation in approximately real-time. These computation methods may involve the use of mapping functions or mappings. Mapping functions may be defined as business logic modules (e.g., machine-executable code) that compute each metric starting from actual or simulated execution data (e.g., operation data from a process). For example, a mapping function may be used to define how to compute a duration metric (e.g., time required to process an item) based on time-stamped data obtained during operation of a process. Such mapping functions may support more than one metric and each metric may depend on one or more mapping functions. In other words, different metrics may be computed by the same mapping and a single metric may require the execution of several mappings to determine its value. Additionally, it should be noted that computations relating to mapping and metrics inherently require a certain amount of completion time. This completion time may be referred to as a computation cost. Accordingly, a high number of calculations relating to mapping and metrics generally results in higher computation costs.